In [4]:
import pandas as pd
import numpy as np
from wordcloud import WordCloud
from PIL import Image
import matplotlib.pyplot as plt
%matplotlib inline

데이터 불러오기¶

In [5]:
df_광주 = pd.read_csv('data/finish/광주.csv')
df_대구 = pd.read_csv('data/finish/대구.csv')
df_대전 = pd.read_csv('data/finish/대전.csv')
df_부산 = pd.read_csv('data/finish/부산.csv')
df_서울 = pd.read_csv('data/finish/서울.csv')
df_울산 = pd.read_csv('data/finish/울산.csv')
df_인천 = pd.read_csv('data/finish/인천.csv')
df_제주 = pd.read_csv('data/finish/제주.csv')
df_대한민국 = pd.read_csv('data/finish/대한민국.csv')

word cloud¶

In [6]:
font_path = 'C:\\Users\\user\\anaconda3\\envs\\kiwi\\Lib\\site-packages\\matplotlib\\mpl-data\\fonts\\malgun.ttf'
In [7]:
preprocessed_광주 = ''.join(map(str, df_광주['preprocessed_data']))
preprocessed_대구 = ''.join(map(str, df_대구['preprocessed_data']))
preprocessed_대전 = ''.join(map(str, df_대전['preprocessed_data']))
preprocessed_부산 = ''.join(map(str, df_부산['preprocessed_data']))
preprocessed_서울 = ''.join(map(str, df_서울['preprocessed_data']))
preprocessed_울산 = ''.join(map(str, df_울산['preprocessed_data']))
preprocessed_인천 = ''.join(map(str, df_인천['preprocessed_data']))
preprocessed_제주 = ''.join(map(str, df_제주['preprocessed_data']))
preprocessed_대한민국 = ''.join(map(str, df_대한민국['preprocessed_data']))

광주¶

In [8]:
cloud = WordCloud(font_path=font_path,
                  background_color = 'white', 
                  width=800, height=800)
my_cloud1 = cloud.generate_from_text(preprocessed_광주)

arr1 = my_cloud1.to_array()

fig = plt.figure(figsize=(10, 10))
plt.imshow(arr1)
plt.axis('off')
plt.show()

대구¶

In [9]:
cloud = WordCloud(font_path=font_path,
                  background_color = 'white', 
                  width=800, height=800)
my_cloud2 = cloud.generate_from_text(preprocessed_대구)

arr1 = my_cloud2.to_array()

fig = plt.figure(figsize=(10, 10))
plt.imshow(arr1)
plt.axis('off')
plt.show()

대전¶

In [10]:
cloud = WordCloud(font_path=font_path,
                  background_color = 'white', 
                  width=800, height=800)
my_cloud1 = cloud.generate_from_text(preprocessed_대전)

arr1 = my_cloud1.to_array()

fig = plt.figure(figsize=(10, 10))
plt.imshow(arr1)
plt.axis('off')
plt.show()

부산¶

In [11]:
cloud = WordCloud(font_path=font_path,
                  background_color = 'white', 
                  width=800, height=800)
my_cloud1 = cloud.generate_from_text(preprocessed_부산)

arr1 = my_cloud1.to_array()

fig = plt.figure(figsize=(10, 10))
plt.imshow(arr1)
plt.axis('off')
plt.show()

서울¶

In [12]:
cloud = WordCloud(font_path=font_path,
                  background_color = 'white', 
                  width=800, height=800)
my_cloud1 = cloud.generate_from_text(preprocessed_서울)

arr1 = my_cloud1.to_array()

fig = plt.figure(figsize=(10, 10))
plt.imshow(arr1)
plt.axis('off')
plt.show()

울산¶

In [13]:
cloud = WordCloud(font_path=font_path,
                  background_color = 'white', 
                  width=800, height=800)
my_cloud1 = cloud.generate_from_text(preprocessed_울산)

arr1 = my_cloud1.to_array()

fig = plt.figure(figsize=(10, 10))
plt.imshow(arr1)
plt.axis('off')
plt.show()

인천¶

In [14]:
cloud = WordCloud(font_path=font_path,
                  background_color = 'white', 
                  width=800, height=800)
my_cloud1 = cloud.generate_from_text(preprocessed_인천)

arr1 = my_cloud1.to_array()

fig = plt.figure(figsize=(10, 10))
plt.imshow(arr1)
plt.axis('off')
plt.show()

제주¶

In [15]:
cloud = WordCloud(font_path=font_path,
                  background_color = 'white', 
                  width=800, height=800)
my_cloud1 = cloud.generate_from_text(preprocessed_제주)

arr1 = my_cloud1.to_array()

fig = plt.figure(figsize=(10, 10))
plt.imshow(arr1)
plt.axis('off')
plt.show()

대한민국¶

In [16]:
cloud = WordCloud(font_path=font_path,
                  background_color = 'white', 
                  width=800, height=800)
my_cloud1 = cloud.generate_from_text(preprocessed_대한민국)

arr1 = my_cloud1.to_array()

fig = plt.figure(figsize=(10, 10))
plt.imshow(arr1)
plt.axis('off')
plt.show()